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1,152 results for “Magnetic resonance imaging”
Carotid Phase-Contrast Magnetic Resonance before Treatment: 4D-Flow versus Standard 2D Imaging
<p>Secchi F, Monti CB, Capra D, Vitale R, Mazzaccaro D, Conti M, Jin N, Giese D, Nano G, Sardanelli F, Marrocco-Trischitta MM. Carotid Phase-Contrast Magnetic Resonance before Treatment: 4D-Flow versus Standard 2D Imaging. Tomography. 2021 Sep 28;7(4):513-522. doi: 10.3390/tomography7040044. PMID: 34698250; PMCID: PMC8544659.</p> <p>Abstract</p> <p>The purpose of this study was to evaluate the level of agreement between flow/velocity data obtained from 2D-phase-contrast (PC) and 4D-flow in patients scheduled for treatment of carotid artery stenosis. Image acquisition was performed using a 1.5 T scanner. We compared mean flow rates, vessel areas, and peak velocities obtained during the acquisition with both techniques in 20 consecutive patients, 15 males and 5 females aged 69 ± 5 years (mean ± standard deviation). There was a good correlation between both techniques for the CCA flow (<em>r</em> = 0.65, <em>p</em> < 0.001), whereas for the ICA flow and ECA flow the correlation was only moderate (<em>r</em> = 0.4, <em>p</em> = 0.011 and <em>r</em> = 0.45, <em>p</em> = 0.003, respectively). Correlations of peak velocities between methods were good for CCA (<em>r</em> = 0.56, <em>p</em> < 0.001) and moderate for ECA (<em>r</em> = 0.41, <em>p</em> = 0.008). There was no correlation for ICA (<em>r</em> = 0.04, <em>p</em> = 0.805). Cross-sectional area values between methods showed no significant correlations for CCA (<em>r</em> = 0.18, <em>p</em> = 0.269), ICA (<em>r</em> = 0.1, <em>p</em> = 0.543), and ECA (<em>r</em> = 0.05, <em>p</em> = 0.767). Conclusion: the 4D-flow imaging provided a good correlation of CCA and a moderate correlation of ICA flow rates against 2D-PC, underestimating peak velocities and overestimating cross-sectional areas in all carotid segments.</p>
Brugada Syndrome: New Insights From Cardiac Magnetic Resonance and Electroanatomical Imaging
<p>Dataset from Pappone C, Santinelli V, Mecarocci V, Tondi L, Ciconte G, Manguso F, Sturla F, Vicedomini G, Micaglio E, Anastasia L, Pica S, Camporeale A, Lombardi M. Brugada Syndrome: New Insights From Cardiac Magnetic Resonance and Electroanatomical Imaging. Circ Arrhythm Electrophysiol. 2021 Nov;14(11):e010004. doi: 10.1161/CIRCEP.121.010004. Epub 2021 Oct 25. PMID: 34693720.</p> <p>Abstract</p> <p><strong>Background: </strong>Brugada syndrome (BrS) is considered a purely electrical disease with variable electrical substrates. Variable rates of mechanical abnormalities have been also reported. Whether exists a link between electrical and mechanical abnormalities has never been previously explored. This investigational physiopathological study aimed to determine the relationship between the substrate size/location, as exposed by ajmaline provocation, and the severity of mechanical abnormalities, as assessed by cardiac magnetic resonance in patients with BrS.</p> <p><strong>Methods: </strong>Twenty-four consecutive high-risk patients with BrS (mean age, 38±11 years, 17 males), presenting with malignant syncope and documented polymorphic ventricular tachycardia/ventricular fibrillation, and candidate to implantable cardioverter defibrillator implantation, underwent cardiac magnetic resonance and electroanatomic maps. During each examination, ajmaline test (1 mg/kg over 5 minutes) was performed. Cardiac magnetic resonance findings were compared with 24 age, sex, and body surface area-matched controls. In patients with BrS, the correlation between the electrical substrate extent and right ventricular regional mechanical abnormalities before/after ajmaline challenge was analyzed.</p> <p><strong>Results: </strong>After ajmaline, patients with BrS showed a reduction of right ventricular (RV) ejection fraction (<em>P</em><0.001), associated with decreased transversal displacement (U, <em>P</em><0.001) and longitudinal strain (ε, <em>P</em><0.001) localized at RV outflow tract. In patients with BrS significant preajmaline/postajmaline changes of transversal displacement (ΔU, <em>P</em><0.001) and longitudinal strain (Δε, <em>P</em><0.001) were found. In the control group, no mechanical changes were observed after ajmaline. The electrical substrate consistently increased after ajmaline from 1.7±2.8 cm<sup>2</sup> to 14.2±7.3 cm<sup>2</sup> (<em>P</em><0.001), extending from the RV outflow tract to the neighboring segments of the RV anterior wall. Postajmaline RV ejection fraction inversely correlated with postajmaline substrate extent (<em>r</em>=-0.830, <em>P</em><0.001). In patients with BrS and normal controls, cardiac magnetic resonance detected neither myocardial fibrosis nor RV outflow tract morphological abnormalities.</p> <p><strong>Conclusions: </strong>BrS is a dynamic RV electromechanical disease, where functional abnormalities correlate with the maximal extent of the substrate size.</p>
Dataset related to article "Diffusion weighted magnetic resonance imaging for kidney cyst volume quantification and non-cystic tissue characterization in ADPKD"
<p>Kidney volumes, demographic features, and median DWI-based parameters related to the individual patients and healthy volunteers included in the study</p>
Dataset related to article "Automated Head Tissue Modelling Based on Structural Magnetic Resonance Images for Electroencephalographic Source Reconstruction"
<p><strong>SCORING SEGMENTATIONS</strong></p> <ul> <li>Qualitative segmentation scores by two raters (rater1; rater2).</li> <li>Scale: excellent (4); good (3); doubtful (2) and failed (1).</li> </ul> <p> </p> <p><strong>DATABASES</strong></p> <ul> <li>IXI database, Imperial College of London (<a href="https://brain-development.org/ixi-dataset/">https://brain-development.org/ixi-dataset/</a>)</li> <li>Autism Brain Imaging Data Exchange (ABIDE) database (<a href="http://fcon_1000.projects.nitrc.org">http://fcon_1000.projects.nitrc.org</a>)</li> <li>SchizConnect database (<a href="http://schizconnect.org">http://schizconnect.org</a>)</li> </ul> <p> </p> <p><strong>SEGMENTATION METHODS</strong></p> <ul> <li>MR-TIM (Taberna et al., 2021), green rows</li> <li>WTS (Liu et al., 2017), red rows</li> </ul> <p> </p> <p><strong>TABLES</strong></p> <p><strong>IXI_young </strong></p> <ul> <li>20 MRI from the IXI database, participants 20–35 years old;</li> <li>MR scanners: Philips Intera 3.0T (HH); Philips Gyroscan Intera 1.5T (G)</li> </ul> <p><strong>IXI_older</strong></p> <ul> <li>20 MRI from the IXI database, participants 60–75 years old;</li> <li>MR scanners: Philips Intera 3.0T (HH); Philips Gyroscan Intera 1.5T (G)</li> </ul> <p><strong>ABIDE</strong></p> <ul> <li>10 MRI from the ABIDE database, participants 18-25 years old;</li> <li>MR scanner: Philips Achieva 3.0T</li> </ul> <p><strong>SchizConnect</strong></p> <ul> <li>10 MRI from the SchizConnect database, participants 19-66 years old;</li> <li>MR scanner: Siemens Trio Tim 3.0T</li> </ul> <p> </p> <p><strong>REFERENCES</strong></p> <p>Liu, Q., Farahibozorg, S., Porcaro, C., Wenderoth, N., & Mantini, D. (2017). Detecting large-scale networks in the human brain using high-density electroencephalography. Hum Brain Mapp, 38(9), 4631-4643. doi:10.1002/hbm.23688</p> <p>Taberna, G. A., Samogin, J., & Mantini, D. (2021). Automated Head Tissue Modelling Based on Structural Magnetic Resonance Images for Electroencephalographic Source Reconstruction. Neuroinformatics. doi:10.1007/s12021-020-09504-5</p>
Dataset related to the article "Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment"
<p>This record contains raw data related to the article "Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment"</p> <p>Abstract</p> <p>Background</p> <p>Segmentation of cardiovascular magnetic resonance (CMR) images is an essential step for evaluating dimensional and functional ventricular parameters as ejection fraction (EF) but may be limited by artifacts, which represent the major challenge to automatically derive clinical information. The aim of this study is to investigate the accuracy of a deep learning (DL) approach for automatic segmentation of cardiac structures from CMR images characterized by magnetic susceptibility artifact in patient with cardiac implanted electronic devices (CIED).</p> <p>Methods</p> <p>In this retrospective study, 230 patients (100 with CIED) who underwent clinically indicated CMR were used to developed and test a DL model. A novel convolutional neural network was proposed to extract the left ventricle (LV) and right (RV) ventricle endocardium and LV epicardium. In order to perform a successful segmentation, it is important the network learns to identify salient image regions even during local magnetic field inhomogeneities. The proposed network takes advantage from a spatial attention module to selectively process the most relevant information and focus on the structures of interest. To improve segmentation, especially for images with artifacts, multiple loss functions were minimized in unison. Segmentation results were assessed against manual tracings and commercial CMR analysis software cvi<sup>42</sup>(Circle Cardiovascular Imaging, Calgary, Alberta, Canada). An external dataset of 56 patients with CIED was used to assess model generalizability.</p> <p>Results</p> <p>In the internal datasets, on image with artifacts, the median Dice coefficients for end-diastolic LV cavity, LV myocardium and RV cavity, were 0.93, 0.77 and 0.87 and 0.91, 0.82, and 0.83 in end-systole, respectively. The proposed method reached higher segmentation accuracy than commercial software, with performance comparable to expert inter-observer variability (bias ± 95%LoA): LVEF 1 ± 8% vs 3 ± 9%, RVEF − 2 ± 15% vs 3 ± 21%. In the external cohort, EF well correlated with manual tracing (intraclass correlation coefficient: LVEF 0.98, RVEF 0.93). The automatic approach was significant faster than manual segmentation in providing cardiac parameters (approximately 1.5 s vs 450 s).</p> <p>Conclusions</p> <p>Experimental results show that the proposed method reached promising performance in cardiac segmentation from CMR images with susceptibility artifacts and alleviates time consuming expert physician contour segmentation.</p>
Dataset related to article "Frozen Section Analysis and Real-Time Magnetic Resonance Imaging of Surgical Specimen Oriented on 3D Printed Tongue Model to Assess Surgical Margins in Oral Tongue Carcinoma: Preliminary Results"
<p>This record contains raw data related to article “Frozen Section Analysis and Real-Time Magnetic Resonance Imaging of Surgical Specimen Oriented on 3D Printed Tongue Model to Assess Surgical Margins in Oral Tongue Carcinoma: Preliminary Results"</p> <p>Abstract</p> <p><strong>Background: </strong> A surgical margin is the apparently healthy tissue around a tumor which has been removed. In oral cavity carcinoma, a negative margin is considered ≥ 5 mm, a close margin between 1 and 5 mm, and a positive margin ≤ 1 mm. Currently, the intraoperative surgical margin status is based on the visual inspection and tissue palpation by the surgeon and intraoperative histopathological assessment of the resection margins by frozen section analysis (FSA). FSA technique is limited and susceptible to sampling errors. Definitive information on the deep resection margins requires postoperative histopathological analysis.</p> <p><strong>Methods: </strong> We described a novel approach for the assessment of intraoperative surgical margins by examining a surgical specimen oriented through a 3D-printed specific patient tongue with real-time Magnetic Resonance Imaging (MRI). We reported the preliminary results of a case series of 10 patients, prospectively enrolled, with oral tongue carcinoma who underwent surgery between February 2020 and April 2021. Two radiologists with 5 and 10 years of experience, respectively, in Head and Neck radiology in consensus evaluated specimen MRI and measured the distance between the tumor and the specimen surface. We performed intraoperative bedside FSA. To compare the performance of bedside FSA and MRI in predicting definitive margin status we computed the weighted sensitivity (SE), specificity (SP), accuracy (ACC), area under the ROC curve (AUC), F1-score, Positive Predictive Value (PPV), and Negative Predictive Value (NPV). To express the concordance between FSA and <em>ex-vivo</em> MRI we reported the jaccard index.</p> <p><strong>Results: </strong> Intraoperative bedside FSA showed SE of 90%, SP of 100%, F1 of 95%, ACC of 0.9%, PPV of 100%, NPV (not a number), and jaccard of 90%, and <em>ex-vivo</em> MRI showed SE of 100%, SP of 100%, F1 of 100%, ACC of 100%, PPV of 100%, NPV of 100%, and jaccard of 100%. These results needed to be validated in a larger sample size of 21- 44 patients.</p> <p><strong>Conclusion: </strong> The presented method allows a more accurate evaluation of surgical margin status, and the first clinical experiences underline the high potential of integrating FSA with <em>ex-vivo</em> MRI of the fresh surgical specimen.</p>
Comparison of Four-Dimensional Magnetic Resonance Imaging Analysis of Left Ventricular Fluid Dynamics and Energetics in Ischemic and Restrictive Cardiomyopathies.
<p>Riva A, Sturla F, Pica S, Camporeale A, Tondi L, Saitta S, Caimi A, Giese D, Palladini G, Milani P, Castelvecchio S, Menicanti L, Redaelli A, Lombardi M, Votta E. Comparison of Four-Dimensional Magnetic Resonance Imaging Analysis of Left Ventricular Fluid Dynamics and Energetics in Ischemic and Restrictive Cardiomyopathies. J Magn Reson Imaging. 2022 Oct;56(4):1157-1170. doi: 10.1002/jmri.28076. Epub 2022 Jan 24. PMID: 35075711; PMCID: PMC9541919.</p> <p>Abstract</p> <p><strong>Background: </strong>Time-resolved three-directional velocity-encoded (4D flow) magnetic resonance imaging (MRI) enables the quantification of left ventricular (LV) intracavitary fluid dynamics and energetics, providing mechanistic insight into LV dysfunctions. Before becoming a support to diagnosis and patient stratification, this analysis should prove capable of discriminating between clearly different LV derangements.</p> <p><strong>Purpose: </strong>To investigate the potential of 4D flow in identifying fluid dynamic and energetics derangements in ischemic and restrictive LV cardiomyopathies.</p> <p><strong>Study type: </strong>Prospective observational study.</p> <p><strong>Population: </strong>Ten patients with post-ischemic cardiomyopathy (ICM), 10 patients with cardiac light-chain cardiac amyloidosis (AL-CA), and 10 healthy controls were included.</p> <p><strong>Field strength/sequence: </strong>1.5 T/balanced steady-state free precession cine and 4D flow sequences.</p> <p><strong>Assessment: </strong>Flow was divided into four components: direct flow (DF), retained inflow, delayed ejection flow, and residual volume (RV). Demographics, LV morphology, flow components, global and regional energetics (volume-normalized kinetic energy [KE<sub>V</sub> ] and viscous energy loss [EL<sub>V</sub> ]), and pressure-derived hemodynamic force (HDF) were compared between the three groups.</p> <p><strong>Statistical tests: </strong>Intergroup differences in flow components were tested by one-way analysis of variance (ANOVA); differences in energetic variables and peak HDF were tested by two-way ANOVA. A P-value of <0.05 was considered significant.</p> <p><strong>Results: </strong>ICM patients exhibited the following statistically significant alterations vs. controls: reduced KE<sub>V</sub> , mostly in the basal region, in systole (-44%) and in diastole (-37%); altered flow components, with reduced DF (-33%) and increased RV (+26%); and reduced basal-apical HDF component on average by 63% at peak systole. AL-CA patients exhibited the following alterations vs. controls: significantly reduced KE<sub>V</sub> at the E-wave peak in the basal segment (-34%); albeit nonstatistically significant, increased peaks and altered time-course of the HDF basal-apical component in diastole and slightly reduced HDF components in systole.</p> <p><strong>Data conclusion: </strong>The analysis of multiple 4D flow-derived parameters highlighted fluid dynamic alterations associated with systolic and diastolic dysfunctions in ICM and AL-CA patients, respectively.</p>
Dynamic magnetic resonance imaging of muscle contraction in facioscapulohumeral muscular dystrophy
<p>This database includes the raw data linked with paper “ Dynamic magnetic resonance imaging of muscle contraction in facioscapulohumeral muscular dystrophy”.<br> Data are related to FSHD patients, who had a confirmed molecular diagnosis. All subjects were scanned on a 3T MAGNETOM Skyra [Siemens Healthineers]. Dynamic scans were performed for both thighs separately in addition to quantitative sequence T2-mapping and Fat Fraction mapping.<br> Quantitative muscle MRI (water-T2 and fat mapping) is being increasingly used to assess disease involvement in muscle disorders, while imaging techniques for assessment of the dynamic and elastic muscle properties have not yet been translated into clinics. In this exploratory study, we quantitatively characterized muscle deformation (strain) in patients affected by facioscapulohumeral muscular dystrophy (FSHD), a prevalent muscular dystrophy, by applying dynamic MRI synchronized with neuromuscular electrical stimulation (NMES). We evaluated the quadriceps muscles in 34 ambulatory patients and 13 healthy controls, at 6-to 12-month time intervals. While a subgroup of patients behaved similarly to controls, for another subgroup the median strain decreased over time (approximately 57% over 1.5 years). Dynamic MRI parameters did not correlate with quantitative MRI. Our results suggest that the evaluation of muscle contraction by NMES-MRI is feasible and could potentially be used to explore the elastic properties and monitor muscle involvement in FSHD and other neuromuscular disorders.</p>
Genomic Evaluation of Multiparametric Magnetic Resonance Imaging -visible and -nonvisible Lesions in Clinically Localized Prostate Cancer
GEO Series GSE101908. Homo sapiens. 42 samples. Type: Methylation profiling by genome tiling array.
Data set from the article Petrini M, Alì M, Cannaò PM, Zambelli D, Cozzi A, Codari M, Malavazos AE, Secchi F, Sardanelli F. Epicardial adipose tissue volume in patients with coronary artery disease or non-ischaemic dilated cardiomyopathy: evaluation with cardiac magnetic resonance imaging. Clin Radiol. 2019 Jan;74(1):81.e1-81.e7. doi: 10.1016/j.crad.2018.09.006. Epub 2018 Oct 15. PMID: 30336943.
<p>Data set from the article Petrini M, Alì M, Cannaò PM, Zambelli D, Cozzi A, Codari M, Malavazos AE, Secchi F, Sardanelli F. Epicardial adipose tissue volume in patients with coronary artery disease or non-ischaemic dilated cardiomyopathy: evaluation with cardiac magnetic resonance imaging. Clin Radiol. 2019 Jan;74(1):81.e1-81.e7. doi: 10.1016/j.crad.2018.09.006. Epub 2018 Oct 15. PMID: 30336943.</p> <p> </p> <p>This is the abstract:</p> <p><strong>Aim: </strong> To compare the amount of epicardial adipose tissue (EAT) in patients with coronary artery disease (CAD) or non-ischaemic dilated cardiomyopathy (NIDCM) with that in patients with negative cardiac magnetic resonance imaging (CMR).</p> <p><strong>Materials and methods: </strong> One hundred and fifty patients (median age 57 years, interquartile range [IQR] 46-66 years) who underwent CMR were evaluated retrospectively: 50 with CAD, 50 with NIDCM, and 50 with negative CMR. For each patient, the EAT mass index (EATMI) to body surface area, end-diastolic volume index (EDVI), end-systolic volume index (ESVI), stroke volume (SV), ejection fraction (EF) for both ventricles, and left ventricle (LV) mass index were estimated. Intra and inter-reader reproducibility was tested in a random subset of 30 patients, 10 for each group. Mann-Whitney U test, Kruskal-Wallis test, Spearman's correlation, and Bland-Altman statistics were used.</p> <p><strong>Results: </strong> The EATMI in CAD patients (median 15.7 g/m<sup>2</sup>, IQR 8.3-25.7) or in NIDCM patients (15.9 g/m<sup>2</sup>, 11.5-18.1) was significantly higher than that in negative CMR patients (9.1 g/m<sup>2</sup>, 6-12; p<0.001 both). No significant difference was found between CAD and NIDCM patients (p=1.000). A correlation between EATMI and LV mass index was found in NIDCM patients (r=0.455, p=0.002). Intra- and inter-reader reproducibility were up to 80% and 72%, respectively.</p> <p><strong>Conclusion: </strong> Patients with NIDCM or CAD exhibited an increased EATMI in comparison to negative CMR patients. CMR can be used to estimate EAT with good reproducibility.</p>
Follow-up assessment of intracranial aneurysms treated with endovascular coiling: comparison of compressed sensing and parallel imaging time-of-flight magnetic resonance angiography
<p>This file contains the data for the paper "Follow-up assessment of intracranial aneurysms treated with endovascular coiling: comparison of compressed sensing and parallel imaging time-of-flight magnetic resonance angiography"</p>
Development and validation of a prediction model using sella magnetic resonance imaging-based radiomics and clinical parameters for diagnosis of growth hormone deficiency and idiopathic short stature: A multicenter, cross-sectional study
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.